MiRFinder: an improved approach and software implementation for genome-wide fast microRNA precursor scans

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2007-01-01
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Huang, Ting-Hua
Fan, Bin
Hu, Zhi-Liang
Li, Kui
Zhao, Shu-Hong
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Rothschild, Max
Distinguished Professor Emeritus
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Animal Science

The Department of Animal Science originally concerned itself with teaching the selection, breeding, feeding and care of livestock. Today it continues this study of the symbiotic relationship between animals and humans, with practical focuses on agribusiness, science, and animal management.

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The Department of Animal Husbandry was established in 1898. The name of the department was changed to the Department of Animal Science in 1962. The Department of Poultry Science was merged into the department in 1971.

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Background: MicroRNAs (miRNAs) are recognized as one of the most important families of noncoding RNAs that serve as important sequence-specific post-transcriptional regulators of gene expression. Identification of miRNAs is an important requirement for understanding the mechanisms of post-transcriptional regulation. Hundreds of miRNAs have been identified by direct cloning and computational approaches in several species. However, there are still many miRNAs that remain to be identified due to lack of either sequence features or robust algorithms to efficiently identify them. Results: We have evaluated features valuable for pre-miRNA prediction, such as the local secondary structure differences of the stem region of miRNA and non-miRNA hairpins. We have also established correlations between different types of mutations and the secondary structures of pre-miRNAs. Utilizing these features and combining some improvements of the current premiRNA prediction methods, we implemented a computational learning method SVM (support vector machine) to build a high throughput and good performance computational pre-miRNA prediction tool called MiRFinder. The tool was designed for genome-wise, pair-wise sequences from two related species. The method built into the tool consisted of two major steps: 1) genome wide search for hairpin candidates and 2) exclusion of the non-robust structures based on analysis of 18 parameters by the SVM method. Results from applying the tool for chicken/human and D. melanogaster/D. pseudoobscura pair-wise genome alignments showed that the tool can be used for genome wide pre-miRNA predictions. Conclusion: The MiRFinder can be a good alternative to current miRNA discovery software. This tool is available at http://www.bioinformatics.org/mirfinder/.

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This is an article from BMC Bioinformatics 8 (2007): 1, doi:10.1186/1471-2105-8-341. Posted with permission.

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Mon Jan 01 00:00:00 UTC 2007
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